Development, evaluation, and implementation of building downwash and plume rise enhancements in AERMOD

ABSTRACT

Recent research has pointed out many reasons why the building downwash formulation in AERMOD needs to be updated due to: overly simplified equations for building wake development; equations that do not account for porous or streamlined structures; a discontinuity in the streamline equation; and over predictions when compared to field observations for buildings with a large footprint. Because of these issues, a research study was initiated in late 2016 with an overall objective of improving the building downwash algorithms in PRIME. The research study involved the use of wind tunnel modeling to develop a database of wind speed and turbulence intensity measurements downwind of various rectangular solids and streamlined (i.e., tanks and towers) structures. Based on those measurements, new equations (PRIME2) were developed to better describe the turbulence increase and velocity deficit in building wakes for these structure types. The PRIME2 building wake equations for turbulence intensity increase and velocity deficit were shown to agree better with wind tunnel observations than the current PRIME equations in AERMOD. The new equations were documented in a journal article and were added to AERMOD’s PRIME subroutine. A new version of AERMOD was then compiled with the new enhanced turbulence and wind speed equations (PRIME2) for evaluation. The key feature of the PRIME2 equations is that building wake enhanced turbulence decays rapidly back to ambient levels above the top of the building versus the current PRIME theory that has constant enhanced turbulence extending up to the height of the wake. This paper provides details on the implementation of the PRIME2 code into AERMOD, PRIME plume rise enhancements, the field databases used to evaluate PRIME2, and the evaluation of PRIME2 against three field databases. The paper shows that AERMOD with the PRIME2 building downwash equations and other enhancements provides the overall best agreement with field observations.

Implications: While AERMOD/PRIME is supposed to provide accurate and unbiased estimates (within a factor of two), recent research has identified several problems with the current building downwash theory in AERMOD and comparisons against field observations have shown significant under and overpredictions. One major problem is that the current theory has the wake effect extending well above the top of the building while new research shows that the wake effect decays rapidly above the top of the building. This could lead AERMOD to underpredict or overpredict ground-level concentrations. Based on recent wind tunnel tests, a new building downwash theory has been developed and documented in a Journal article. This theory has been added to the PRIME building downwash algorithm in AERMOD and is currently included as an Alpha option in AERMOD. This paper evaluates that new theory against field observations and demonstrates that the updated theory provides better agreement with field observations than the current AERMOD. This paper points out that research and development of model building downwash improvements should be an ongoing process to help ensure a “sustainable” future where these improvements can ultimately provide a model with unbiased performance and thereby allow for responsible industrial development. This study has shown that improvements can be made in a rather quick manner and be included as Alpha options in EPA model updates. The next challenge is to transition these options from Alpha to Beta options and then finally to a default status.

Acknowledgment

The authors wish to acknowledge the financial and technical support from the American Petroleum Institute’s (API) Air Model Group as well as the technical support and review from the PRIME2 subcommittee of the Atmospheric Modeling and Meteorology Committee of the A&WMA.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All model input files and field observations for the Bowline Point and Alaska database can be found at the following link on EPA’s Support Center for Regulatory Air Modeling (SCRAM) web site under the AERMOD Modeling System’s “Model Evaluation Data Bases.”

https://www.epa.gov/scram/air-quality-dispersion-modeling-preferred-and-recommended-models#aermod.

All model input files and field observations for the Balko, OK database are available from the corresponding author, [RLP], upon reasonable request.

Additional information

Funding

This work was supported by the American Petroleum Institute [2021-114595].

Notes on contributors

Ron L. Petersen

Ron L. Petersen, Ph.D., CCM. President of Petersen Research and Consulting LLC. Dr. Petersen serves as Chair of the PRIME2 subcommittee of the Air and Waste Management Association’s (A&WMA) Atmospheric Modeling and Meteorology Committee.

James O. Paumier

James O. Paumier, Consultant. Mr. Paumier worked at an engineering and environmental consulting firm that had contracts with EPA in the maintenance and enhancement of the AERMOD Dispersion Modeling System.

Sergio A. Guerra

Sergio A. Guerra, Ph.D. Deputy Director for Stationary Sources, Air Pollution Control Division Of Colorado Department of Public Health and Environment. Dr. Guerra serves as the Chair of the Atmospheric Modeling and Meteorology Committee of the A&WMA.